Overview

Brought to you by YData

Dataset statistics

Number of variables32
Number of observations37609
Missing cells147608
Missing cells (%)12.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory59.0 MiB
Average record size in memory1.6 KiB

Variable types

Numeric1
Text21
Categorical6
Unsupported2
Boolean2

Alerts

naics has constant value "0"Constant
naics_title has constant value "cross-industry"Constant
i_group has constant value "cross-industry"Constant
own_code has constant value "1235"Constant
annual has constant value "True"Constant
hourly has constant value "True"Constant
area is highly overall correlated with area_typeHigh correlation
area_type is highly overall correlated with areaHigh correlation
area_type is highly imbalanced (82.2%)Imbalance
o_group is highly imbalanced (86.3%)Imbalance
pct_total has 37609 (100.0%) missing valuesMissing
pct_rpt has 37609 (100.0%) missing valuesMissing
annual has 34943 (92.9%) missing valuesMissing
hourly has 37447 (99.6%) missing valuesMissing
pct_total is an unsupported type, check if it needs cleaning or further analysisUnsupported
pct_rpt is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2025-11-11 02:56:00.427687
Analysis finished2025-11-11 02:56:02.757043
Duration2.33 seconds
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

area
Real number (ℝ)

High correlation 

Distinct54
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.176633
Minimum1
Maximum78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size293.9 KiB
2025-11-10T21:56:02.840396image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q117
median30
Q344
95-th percentile55
Maximum78
Range77
Interquartile range (IQR)27

Descriptive statistics

Standard deviation16.823968
Coefficient of variation (CV)0.55751639
Kurtosis-0.5641297
Mean30.176633
Median Absolute Deviation (MAD)13
Skewness0.22257039
Sum1134913
Variance283.04588
MonotonicityIncreasing
2025-11-10T21:56:02.916073image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6829
 
2.2%
48827
 
2.2%
42818
 
2.2%
36817
 
2.2%
12814
 
2.2%
39810
 
2.2%
26806
 
2.1%
37795
 
2.1%
53794
 
2.1%
51792
 
2.1%
Other values (44)29507
78.5%
ValueCountFrequency (%)
1736
2.0%
2564
1.5%
4743
2.0%
5698
1.9%
6829
2.2%
8765
2.0%
9714
1.9%
10570
1.5%
11522
1.4%
12814
2.2%
ValueCountFrequency (%)
78193
 
0.5%
72583
1.6%
66233
 
0.6%
56536
1.4%
55776
2.1%
54665
1.8%
53794
2.1%
51792
2.1%
50584
1.6%
49740
2.0%
Distinct54
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2025-11-10T21:56:03.026765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length12
Mean length8.6317371
Min length4

Characters and Unicode

Total characters324631
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowalabama
2nd rowalabama
3rd rowalabama
4th rowalabama
5th rowalabama
ValueCountFrequency (%)
new2914
 
6.3%
carolina1554
 
3.4%
virginia1457
 
3.1%
north1383
 
3.0%
south1362
 
2.9%
dakota1191
 
2.6%
california829
 
1.8%
texas827
 
1.8%
pennsylvania818
 
1.8%
york817
 
1.8%
Other values (50)33175
71.6%
2025-11-10T21:56:03.240611image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a44318
13.7%
i35100
10.8%
n31976
 
9.8%
o28324
 
8.7%
s24201
 
7.5%
e20680
 
6.4%
r17894
 
5.5%
t15034
 
4.6%
l11719
 
3.6%
c10667
 
3.3%
Other values (16)84718
26.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)324631
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a44318
13.7%
i35100
10.8%
n31976
 
9.8%
o28324
 
8.7%
s24201
 
7.5%
e20680
 
6.4%
r17894
 
5.5%
t15034
 
4.6%
l11719
 
3.6%
c10667
 
3.3%
Other values (16)84718
26.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)324631
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a44318
13.7%
i35100
10.8%
n31976
 
9.8%
o28324
 
8.7%
s24201
 
7.5%
e20680
 
6.4%
r17894
 
5.5%
t15034
 
4.6%
l11719
 
3.6%
c10667
 
3.3%
Other values (16)84718
26.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)324631
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a44318
13.7%
i35100
10.8%
n31976
 
9.8%
o28324
 
8.7%
s24201
 
7.5%
e20680
 
6.4%
r17894
 
5.5%
t15034
 
4.6%
l11719
 
3.6%
c10667
 
3.3%
Other values (16)84718
26.1%

area_type
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.1 MiB
2
36600 
3
 
1009

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters37609
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
236600
97.3%
31009
 
2.7%

Length

2025-11-10T21:56:03.302969image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-10T21:56:03.357390image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
236600
97.3%
31009
 
2.7%

Most occurring characters

ValueCountFrequency (%)
236600
97.3%
31009
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)37609
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
236600
97.3%
31009
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)37609
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
236600
97.3%
31009
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)37609
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
236600
97.3%
31009
 
2.7%
Distinct54
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.1 MiB
2025-11-10T21:56:03.447386image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters75218
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowal
2nd rowal
3rd rowal
4th rowal
5th rowal
ValueCountFrequency (%)
ca829
 
2.2%
tx827
 
2.2%
pa818
 
2.2%
ny817
 
2.2%
fl814
 
2.2%
oh810
 
2.2%
mi806
 
2.1%
nc795
 
2.1%
wa794
 
2.1%
va792
 
2.1%
Other values (44)29507
78.5%
2025-11-10T21:56:03.598105image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a8980
 
11.9%
n8017
 
10.7%
m6519
 
8.7%
i5910
 
7.9%
c4384
 
5.8%
t4282
 
5.7%
o3849
 
5.1%
d3716
 
4.9%
l3054
 
4.1%
v2937
 
3.9%
Other values (14)23570
31.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)75218
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a8980
 
11.9%
n8017
 
10.7%
m6519
 
8.7%
i5910
 
7.9%
c4384
 
5.8%
t4282
 
5.7%
o3849
 
5.1%
d3716
 
4.9%
l3054
 
4.1%
v2937
 
3.9%
Other values (14)23570
31.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)75218
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a8980
 
11.9%
n8017
 
10.7%
m6519
 
8.7%
i5910
 
7.9%
c4384
 
5.8%
t4282
 
5.7%
o3849
 
5.1%
d3716
 
4.9%
l3054
 
4.1%
v2937
 
3.9%
Other values (14)23570
31.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)75218
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a8980
 
11.9%
n8017
 
10.7%
m6519
 
8.7%
i5910
 
7.9%
c4384
 
5.8%
t4282
 
5.7%
o3849
 
5.1%
d3716
 
4.9%
l3054
 
4.1%
v2937
 
3.9%
Other values (14)23570
31.3%

naics
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.1 MiB
0
37609 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters37609
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
037609
100.0%

Length

2025-11-10T21:56:03.658592image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-10T21:56:03.703679image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
037609
100.0%

Most occurring characters

ValueCountFrequency (%)
037609
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)37609
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
037609
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)37609
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
037609
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)37609
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
037609
100.0%

naics_title
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
cross-industry
37609 

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters526526
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowcross-industry
2nd rowcross-industry
3rd rowcross-industry
4th rowcross-industry
5th rowcross-industry

Common Values

ValueCountFrequency (%)
cross-industry37609
100.0%

Length

2025-11-10T21:56:03.751867image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-10T21:56:03.797182image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
cross-industry37609
100.0%

Most occurring characters

ValueCountFrequency (%)
s112827
21.4%
r75218
14.3%
c37609
 
7.1%
o37609
 
7.1%
-37609
 
7.1%
i37609
 
7.1%
n37609
 
7.1%
d37609
 
7.1%
u37609
 
7.1%
t37609
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)526526
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s112827
21.4%
r75218
14.3%
c37609
 
7.1%
o37609
 
7.1%
-37609
 
7.1%
i37609
 
7.1%
n37609
 
7.1%
d37609
 
7.1%
u37609
 
7.1%
t37609
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)526526
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s112827
21.4%
r75218
14.3%
c37609
 
7.1%
o37609
 
7.1%
-37609
 
7.1%
i37609
 
7.1%
n37609
 
7.1%
d37609
 
7.1%
u37609
 
7.1%
t37609
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)526526
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s112827
21.4%
r75218
14.3%
c37609
 
7.1%
o37609
 
7.1%
-37609
 
7.1%
i37609
 
7.1%
n37609
 
7.1%
d37609
 
7.1%
u37609
 
7.1%
t37609
 
7.1%

i_group
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
cross-industry
37609 

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters526526
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowcross-industry
2nd rowcross-industry
3rd rowcross-industry
4th rowcross-industry
5th rowcross-industry

Common Values

ValueCountFrequency (%)
cross-industry37609
100.0%

Length

2025-11-10T21:56:03.845859image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-10T21:56:03.890977image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
cross-industry37609
100.0%

Most occurring characters

ValueCountFrequency (%)
s112827
21.4%
r75218
14.3%
c37609
 
7.1%
o37609
 
7.1%
-37609
 
7.1%
i37609
 
7.1%
n37609
 
7.1%
d37609
 
7.1%
u37609
 
7.1%
t37609
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)526526
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s112827
21.4%
r75218
14.3%
c37609
 
7.1%
o37609
 
7.1%
-37609
 
7.1%
i37609
 
7.1%
n37609
 
7.1%
d37609
 
7.1%
u37609
 
7.1%
t37609
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)526526
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s112827
21.4%
r75218
14.3%
c37609
 
7.1%
o37609
 
7.1%
-37609
 
7.1%
i37609
 
7.1%
n37609
 
7.1%
d37609
 
7.1%
u37609
 
7.1%
t37609
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)526526
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s112827
21.4%
r75218
14.3%
c37609
 
7.1%
o37609
 
7.1%
-37609
 
7.1%
i37609
 
7.1%
n37609
 
7.1%
d37609
 
7.1%
u37609
 
7.1%
t37609
 
7.1%

own_code
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
1235
37609 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters150436
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1235
2nd row1235
3rd row1235
4th row1235
5th row1235

Common Values

ValueCountFrequency (%)
123537609
100.0%

Length

2025-11-10T21:56:03.939358image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-10T21:56:03.987897image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
123537609
100.0%

Most occurring characters

ValueCountFrequency (%)
137609
25.0%
237609
25.0%
337609
25.0%
537609
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)150436
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
137609
25.0%
237609
25.0%
337609
25.0%
537609
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)150436
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
137609
25.0%
237609
25.0%
337609
25.0%
537609
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)150436
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
137609
25.0%
237609
25.0%
337609
25.0%
537609
25.0%
Distinct854
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2025-11-10T21:56:04.132676image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters263263
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row00-0000
2nd row11-0000
3rd row11-1011
4th row11-1021
5th row11-1031
ValueCountFrequency (%)
00-000054
 
0.1%
43-408154
 
0.1%
43-000054
 
0.1%
43-301154
 
0.1%
43-302154
 
0.1%
43-303154
 
0.1%
43-305154
 
0.1%
43-405154
 
0.1%
43-417154
 
0.1%
43-902154
 
0.1%
Other values (844)37069
98.6%
2025-11-10T21:56:04.337076image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
157208
21.7%
-37609
14.3%
035050
13.3%
233492
12.7%
326635
10.1%
923264
8.8%
417815
 
6.8%
517356
 
6.6%
79404
 
3.6%
63547
 
1.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)263263
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
157208
21.7%
-37609
14.3%
035050
13.3%
233492
12.7%
326635
10.1%
923264
8.8%
417815
 
6.8%
517356
 
6.6%
79404
 
3.6%
63547
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)263263
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
157208
21.7%
-37609
14.3%
035050
13.3%
233492
12.7%
326635
10.1%
923264
8.8%
417815
 
6.8%
517356
 
6.6%
79404
 
3.6%
63547
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)263263
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
157208
21.7%
-37609
14.3%
035050
13.3%
233492
12.7%
326635
10.1%
923264
8.8%
417815
 
6.8%
517356
 
6.6%
79404
 
3.6%
63547
 
1.3%
Distinct854
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size3.3 MiB
2025-11-10T21:56:04.450026image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length112
Median length75
Mean length35.15725
Min length6

Characters and Unicode

Total characters1322229
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowall occupations
2nd rowmanagement occupations
3rd rowchief executives
4th rowgeneral and operations managers
5th rowlegislators
ValueCountFrequency (%)
and21836
 
13.7%
workers3923
 
2.5%
other3170
 
2.0%
operators3125
 
2.0%
all2957
 
1.9%
teachers2390
 
1.5%
technicians2360
 
1.5%
except1873
 
1.2%
postsecondary1793
 
1.1%
machine1774
 
1.1%
Other values (1097)114080
71.6%
2025-11-10T21:56:04.636572image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e134227
10.2%
121672
 
9.2%
a113041
 
8.5%
s112517
 
8.5%
r104784
 
7.9%
n95406
 
7.2%
i91936
 
7.0%
t90408
 
6.8%
o72084
 
5.5%
c66741
 
5.0%
Other values (21)319413
24.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)1322229
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e134227
10.2%
121672
 
9.2%
a113041
 
8.5%
s112517
 
8.5%
r104784
 
7.9%
n95406
 
7.2%
i91936
 
7.0%
t90408
 
6.8%
o72084
 
5.5%
c66741
 
5.0%
Other values (21)319413
24.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1322229
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e134227
10.2%
121672
 
9.2%
a113041
 
8.5%
s112517
 
8.5%
r104784
 
7.9%
n95406
 
7.2%
i91936
 
7.0%
t90408
 
6.8%
o72084
 
5.5%
c66741
 
5.0%
Other values (21)319413
24.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1322229
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e134227
10.2%
121672
 
9.2%
a113041
 
8.5%
s112517
 
8.5%
r104784
 
7.9%
n95406
 
7.2%
i91936
 
7.0%
t90408
 
6.8%
o72084
 
5.5%
c66741
 
5.0%
Other values (21)319413
24.2%

o_group
Categorical

Imbalance 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
detailed
36367 
major
 
1188
total
 
54

Length

Max length8
Median length8
Mean length7.900928
Min length5

Characters and Unicode

Total characters297146
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowtotal
2nd rowmajor
3rd rowdetailed
4th rowdetailed
5th rowdetailed

Common Values

ValueCountFrequency (%)
detailed36367
96.7%
major1188
 
3.2%
total54
 
0.1%

Length

2025-11-10T21:56:04.745100image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-10T21:56:04.795433image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
detailed36367
96.7%
major1188
 
3.2%
total54
 
0.1%

Most occurring characters

ValueCountFrequency (%)
d72734
24.5%
e72734
24.5%
a37609
12.7%
t36475
12.3%
l36421
12.3%
i36367
12.2%
o1242
 
0.4%
m1188
 
0.4%
j1188
 
0.4%
r1188
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)297146
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
d72734
24.5%
e72734
24.5%
a37609
12.7%
t36475
12.3%
l36421
12.3%
i36367
12.2%
o1242
 
0.4%
m1188
 
0.4%
j1188
 
0.4%
r1188
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)297146
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
d72734
24.5%
e72734
24.5%
a37609
12.7%
t36475
12.3%
l36421
12.3%
i36367
12.2%
o1242
 
0.4%
m1188
 
0.4%
j1188
 
0.4%
r1188
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)297146
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
d72734
24.5%
e72734
24.5%
a37609
12.7%
t36475
12.3%
l36421
12.3%
i36367
12.2%
o1242
 
0.4%
m1188
 
0.4%
j1188
 
0.4%
r1188
 
0.4%

tot_emp
Text

Distinct3995
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:04.930713image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.4316254
Min length2

Characters and Unicode

Total characters129060
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2242 ?
Unique (%)6.0%

Sample

1st row2091480
2nd row110240
3rd row830
4th row32370
5th row1120
ValueCountFrequency (%)
1353
 
3.6%
40688
 
1.8%
60623
 
1.7%
70612
 
1.6%
50608
 
1.6%
90538
 
1.4%
80491
 
1.3%
110489
 
1.3%
100482
 
1.3%
130449
 
1.2%
Other values (3985)31276
83.2%
2025-11-10T21:56:05.143493image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
042318
32.8%
116774
 
13.0%
211629
 
9.0%
310019
 
7.8%
49192
 
7.1%
58312
 
6.4%
67778
 
6.0%
77145
 
5.5%
86804
 
5.3%
96383
 
4.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)129060
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
042318
32.8%
116774
 
13.0%
211629
 
9.0%
310019
 
7.8%
49192
 
7.1%
58312
 
6.4%
67778
 
6.0%
77145
 
5.5%
86804
 
5.3%
96383
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)129060
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
042318
32.8%
116774
 
13.0%
211629
 
9.0%
310019
 
7.8%
49192
 
7.1%
58312
 
6.4%
67778
 
6.0%
77145
 
5.5%
86804
 
5.3%
96383
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)129060
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
042318
32.8%
116774
 
13.0%
211629
 
9.0%
310019
 
7.8%
49192
 
7.1%
58312
 
6.4%
67778
 
6.0%
77145
 
5.5%
86804
 
5.3%
96383
 
4.9%
Distinct501
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:05.297630image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.2187242
Min length1

Characters and Unicode

Total characters121053
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0.9
3rd row17.6
4th row1.6
5th row8.7
ValueCountFrequency (%)
1353
 
3.6%
0380
 
1.0%
6.5241
 
0.6%
4239
 
0.6%
4.7232
 
0.6%
2.5230
 
0.6%
3.4230
 
0.6%
5.1229
 
0.6%
4.9226
 
0.6%
6.9226
 
0.6%
Other values (491)34023
90.5%
2025-11-10T21:56:05.509039image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
.32226
26.6%
117800
14.7%
211961
 
9.9%
39711
 
8.0%
48523
 
7.0%
57368
 
6.1%
67211
 
6.0%
76878
 
5.7%
86618
 
5.5%
96255
 
5.2%
Other values (2)6502
 
5.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)121053
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
.32226
26.6%
117800
14.7%
211961
 
9.9%
39711
 
8.0%
48523
 
7.0%
57368
 
6.1%
67211
 
6.0%
76878
 
5.7%
86618
 
5.5%
96255
 
5.2%
Other values (2)6502
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)121053
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
.32226
26.6%
117800
14.7%
211961
 
9.9%
39711
 
8.0%
48523
 
7.0%
57368
 
6.1%
67211
 
6.0%
76878
 
5.7%
86618
 
5.5%
96255
 
5.2%
Other values (2)6502
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)121053
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
.32226
26.6%
117800
14.7%
211961
 
9.9%
39711
 
8.0%
48523
 
7.0%
57368
 
6.1%
67211
 
6.0%
76878
 
5.7%
86618
 
5.5%
96255
 
5.2%
Other values (2)6502
 
5.4%
Distinct7322
Distinct (%)19.5%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:05.675208image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.8407828
Min length1

Characters and Unicode

Total characters182057
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4164 ?
Unique (%)11.1%

Sample

1st row1000
2nd row52.708
3rd row0.396
4th row15.476
5th row0.533
ValueCountFrequency (%)
1353
 
3.6%
0.029106
 
0.3%
0.022104
 
0.3%
0.05295
 
0.3%
0.07593
 
0.2%
0.03792
 
0.2%
0.05791
 
0.2%
0.06988
 
0.2%
0.06386
 
0.2%
0.04886
 
0.2%
Other values (7312)35415
94.2%
2025-11-10T21:56:05.899774image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
036492
20.0%
.36185
19.9%
119482
10.7%
214888
8.2%
312527
 
6.9%
411093
 
6.1%
510590
 
5.8%
69984
 
5.5%
79783
 
5.4%
89334
 
5.1%
Other values (2)11699
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)182057
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
036492
20.0%
.36185
19.9%
119482
10.7%
214888
8.2%
312527
 
6.9%
411093
 
6.1%
510590
 
5.8%
69984
 
5.5%
79783
 
5.4%
89334
 
5.1%
Other values (2)11699
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)182057
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
036492
20.0%
.36185
19.9%
119482
10.7%
214888
8.2%
312527
 
6.9%
411093
 
6.1%
510590
 
5.8%
69984
 
5.5%
79783
 
5.4%
89334
 
5.1%
Other values (2)11699
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)182057
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
036492
20.0%
.36185
19.9%
119482
10.7%
214888
8.2%
312527
 
6.9%
411093
 
6.1%
510590
 
5.8%
69984
 
5.5%
79783
 
5.4%
89334
 
5.1%
Other values (2)11699
 
6.4%
Distinct852
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:06.066364image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.8118004
Min length1

Characters and Unicode

Total characters143358
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique283 ?
Unique (%)0.8%

Sample

1st row1
2nd row0.74
3rd row0.29
4th row0.67
5th row3.1
ValueCountFrequency (%)
1353
 
3.6%
0.92356
 
0.9%
0.89355
 
0.9%
0.93353
 
0.9%
0.96352
 
0.9%
1351
 
0.9%
0.91350
 
0.9%
0.94347
 
0.9%
0.87347
 
0.9%
1.02344
 
0.9%
Other values (842)33101
88.0%
2025-11-10T21:56:06.287395image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
.35846
25.0%
023313
16.3%
120261
14.1%
29008
 
6.3%
97666
 
5.3%
37656
 
5.3%
87533
 
5.3%
77492
 
5.2%
67376
 
5.1%
47257
 
5.1%
Other values (2)9950
 
6.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)143358
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
.35846
25.0%
023313
16.3%
120261
14.1%
29008
 
6.3%
97666
 
5.3%
37656
 
5.3%
87533
 
5.3%
77492
 
5.2%
67376
 
5.1%
47257
 
5.1%
Other values (2)9950
 
6.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)143358
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
.35846
25.0%
023313
16.3%
120261
14.1%
29008
 
6.3%
97666
 
5.3%
37656
 
5.3%
87533
 
5.3%
77492
 
5.2%
67376
 
5.1%
47257
 
5.1%
Other values (2)9950
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)143358
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
.35846
25.0%
023313
16.3%
120261
14.1%
29008
 
6.3%
97666
 
5.3%
37656
 
5.3%
87533
 
5.3%
77492
 
5.2%
67376
 
5.1%
47257
 
5.1%
Other values (2)9950
 
6.9%

pct_total
Unsupported

Missing  Rejected  Unsupported 

Missing37609
Missing (%)100.0%
Memory size293.9 KiB

pct_rpt
Unsupported

Missing  Rejected  Unsupported 

Missing37609
Missing (%)100.0%
Memory size293.9 KiB

h_mean
Text

Distinct6713
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:06.450066image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.573985
Min length1

Characters and Unicode

Total characters172023
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2070 ?
Unique (%)5.5%

Sample

1st row26.61
2nd row57.05
3rd row99.61
4th row64.8
5th row*
ValueCountFrequency (%)
3128
 
8.3%
22.3527
 
0.1%
21.1427
 
0.1%
20.6426
 
0.1%
24.4726
 
0.1%
20.9525
 
0.1%
24.425
 
0.1%
21.8525
 
0.1%
20.3825
 
0.1%
22.6725
 
0.1%
Other values (6702)34250
91.1%
2025-11-10T21:56:06.671073image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
.34131
19.8%
223689
13.8%
317232
10.0%
117205
10.0%
414332
8.3%
512033
 
7.0%
611453
 
6.7%
710844
 
6.3%
810746
 
6.2%
910545
 
6.1%
Other values (3)9813
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)172023
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
.34131
19.8%
223689
13.8%
317232
10.0%
117205
10.0%
414332
8.3%
512033
 
7.0%
611453
 
6.7%
710844
 
6.3%
810746
 
6.2%
910545
 
6.1%
Other values (3)9813
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)172023
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
.34131
19.8%
223689
13.8%
317232
10.0%
117205
10.0%
414332
8.3%
512033
 
7.0%
611453
 
6.7%
710844
 
6.3%
810746
 
6.2%
910545
 
6.1%
Other values (3)9813
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)172023
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
.34131
19.8%
223689
13.8%
317232
10.0%
117205
10.0%
414332
8.3%
512033
 
7.0%
611453
 
6.7%
710844
 
6.3%
810746
 
6.2%
910545
 
6.1%
Other values (3)9813
 
5.7%

a_mean
Text

Distinct11304
Distinct (%)30.1%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:06.814672image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0847669
Min length1

Characters and Unicode

Total characters191233
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3901 ?
Unique (%)10.4%

Sample

1st row55350
2nd row118670
3rd row207190
4th row134790
5th row36570
ValueCountFrequency (%)
635
 
1.7%
4857016
 
< 0.1%
3943016
 
< 0.1%
4590015
 
< 0.1%
5076015
 
< 0.1%
5605015
 
< 0.1%
5835015
 
< 0.1%
5220015
 
< 0.1%
4411015
 
< 0.1%
4528015
 
< 0.1%
Other values (11293)36837
97.9%
2025-11-10T21:56:07.012778image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
049672
26.0%
418772
 
9.8%
517659
 
9.2%
117251
 
9.0%
616042
 
8.4%
315884
 
8.3%
714802
 
7.7%
813773
 
7.2%
213387
 
7.0%
913356
 
7.0%
Other values (2)635
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)191233
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
049672
26.0%
418772
 
9.8%
517659
 
9.2%
117251
 
9.0%
616042
 
8.4%
315884
 
8.3%
714802
 
7.7%
813773
 
7.2%
213387
 
7.0%
913356
 
7.0%
Other values (2)635
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)191233
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
049672
26.0%
418772
 
9.8%
517659
 
9.2%
117251
 
9.0%
616042
 
8.4%
315884
 
8.3%
714802
 
7.7%
813773
 
7.2%
213387
 
7.0%
913356
 
7.0%
Other values (2)635
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)191233
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
049672
26.0%
418772
 
9.8%
517659
 
9.2%
117251
 
9.0%
616042
 
8.4%
315884
 
8.3%
714802
 
7.7%
813773
 
7.2%
213387
 
7.0%
913356
 
7.0%
Other values (2)635
 
0.3%
Distinct293
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 MiB
2025-11-10T21:56:07.190538image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.8386025
Min length1

Characters and Unicode

Total characters106757
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.1%

Sample

1st row0.3
2nd row0.7
3rd row4.6
4th row1.6
5th row3.8
ValueCountFrequency (%)
1.11046
 
2.8%
1.4993
 
2.6%
0.9991
 
2.6%
0.8991
 
2.6%
1.2985
 
2.6%
0.7981
 
2.6%
1.3940
 
2.5%
1918
 
2.4%
1.6882
 
2.3%
1.5878
 
2.3%
Other values (283)28004
74.5%
2025-11-10T21:56:07.429957image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
.33312
31.2%
115445
14.5%
210926
 
10.2%
38148
 
7.6%
47027
 
6.6%
06144
 
5.8%
55901
 
5.5%
65458
 
5.1%
75028
 
4.7%
84668
 
4.4%
Other values (2)4700
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)106757
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
.33312
31.2%
115445
14.5%
210926
 
10.2%
38148
 
7.6%
47027
 
6.6%
06144
 
5.8%
55901
 
5.5%
65458
 
5.1%
75028
 
4.7%
84668
 
4.4%
Other values (2)4700
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)106757
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
.33312
31.2%
115445
14.5%
210926
 
10.2%
38148
 
7.6%
47027
 
6.6%
06144
 
5.8%
55901
 
5.5%
65458
 
5.1%
75028
 
4.7%
84668
 
4.4%
Other values (2)4700
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)106757
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
.33312
31.2%
115445
14.5%
210926
 
10.2%
38148
 
7.6%
47027
 
6.6%
06144
 
5.8%
55901
 
5.5%
65458
 
5.1%
75028
 
4.7%
84668
 
4.4%
Other values (2)4700
 
4.4%

h_pct10
Text

Distinct4259
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:07.583428image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.4513813
Min length1

Characters and Unicode

Total characters167412
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1054 ?
Unique (%)2.8%

Sample

1st row11.31
2nd row24.57
3rd row50.46
4th row24.24
5th row*
ValueCountFrequency (%)
3128
 
8.3%
15256
 
0.7%
14172
 
0.5%
17123
 
0.3%
12116
 
0.3%
9.5115
 
0.3%
15.13113
 
0.3%
20.4890
 
0.2%
15.6985
 
0.2%
1883
 
0.2%
Other values (4248)33328
88.6%
2025-11-10T21:56:07.792882image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
.33129
19.8%
128703
17.1%
219662
11.7%
313589
8.1%
411188
 
6.7%
710862
 
6.5%
810713
 
6.4%
510530
 
6.3%
610261
 
6.1%
99622
 
5.7%
Other values (3)9153
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)167412
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
.33129
19.8%
128703
17.1%
219662
11.7%
313589
8.1%
411188
 
6.7%
710862
 
6.5%
810713
 
6.4%
510530
 
6.3%
610261
 
6.1%
99622
 
5.7%
Other values (3)9153
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)167412
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
.33129
19.8%
128703
17.1%
219662
11.7%
313589
8.1%
411188
 
6.7%
710862
 
6.5%
810713
 
6.4%
510530
 
6.3%
610261
 
6.1%
99622
 
5.7%
Other values (3)9153
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)167412
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
.33129
19.8%
128703
17.1%
219662
11.7%
313589
8.1%
411188
 
6.7%
710862
 
6.5%
810713
 
6.4%
510530
 
6.3%
610261
 
6.1%
99622
 
5.7%
Other values (3)9153
 
5.5%

h_pct25
Text

Distinct5028
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:07.958431image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.4836342
Min length1

Characters and Unicode

Total characters168625
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1315 ?
Unique (%)3.5%

Sample

1st row14.74
2nd row35.03
3rd row62.96
4th row35.92
5th row*
ValueCountFrequency (%)
3277
 
8.7%
15118
 
0.3%
1477
 
0.2%
1875
 
0.2%
1771
 
0.2%
2058
 
0.2%
19.0257
 
0.2%
2556
 
0.1%
2153
 
0.1%
2251
 
0.1%
Other values (5017)33716
89.6%
2025-11-10T21:56:08.228436image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
.33347
19.8%
123714
14.1%
222336
13.2%
314946
8.9%
411627
 
6.9%
711280
 
6.7%
811150
 
6.6%
510403
 
6.2%
610206
 
6.1%
910048
 
6.0%
Other values (3)9568
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)168625
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
.33347
19.8%
123714
14.1%
222336
13.2%
314946
8.9%
411627
 
6.9%
711280
 
6.7%
811150
 
6.6%
510403
 
6.2%
610206
 
6.1%
910048
 
6.0%
Other values (3)9568
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)168625
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
.33347
19.8%
123714
14.1%
222336
13.2%
314946
8.9%
411627
 
6.9%
711280
 
6.7%
811150
 
6.6%
510403
 
6.2%
610206
 
6.1%
910048
 
6.0%
Other values (3)9568
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)168625
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
.33347
19.8%
123714
14.1%
222336
13.2%
314946
8.9%
411627
 
6.9%
711280
 
6.7%
811150
 
6.6%
510403
 
6.2%
610206
 
6.1%
910048
 
6.0%
Other values (3)9568
 
5.7%
Distinct5914
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:08.393190image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.4800181
Min length1

Characters and Unicode

Total characters168489
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1545 ?
Unique (%)4.1%

Sample

1st row21.07
2nd row48.39
3rd row79.04
4th row51.12
5th row*
ValueCountFrequency (%)
3561
 
9.5%
2070
 
0.2%
2557
 
0.2%
23.5644
 
0.1%
1844
 
0.1%
28.8241
 
0.1%
2339
 
0.1%
2136
 
0.1%
1536
 
0.1%
2235
 
0.1%
Other values (5903)33646
89.5%
2025-11-10T21:56:08.611875image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
.33284
19.8%
223292
13.8%
118087
10.7%
316578
9.8%
412986
 
7.7%
811227
 
6.7%
711217
 
6.7%
510807
 
6.4%
610776
 
6.4%
910151
 
6.0%
Other values (3)10084
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)168489
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
.33284
19.8%
223292
13.8%
118087
10.7%
316578
9.8%
412986
 
7.7%
811227
 
6.7%
711217
 
6.7%
510807
 
6.4%
610776
 
6.4%
910151
 
6.0%
Other values (3)10084
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)168489
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
.33284
19.8%
223292
13.8%
118087
10.7%
316578
9.8%
412986
 
7.7%
811227
 
6.7%
711217
 
6.7%
510807
 
6.4%
610776
 
6.4%
910151
 
6.0%
Other values (3)10084
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)168489
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
.33284
19.8%
223292
13.8%
118087
10.7%
316578
9.8%
412986
 
7.7%
811227
 
6.7%
711217
 
6.7%
510807
 
6.4%
610776
 
6.4%
910151
 
6.0%
Other values (3)10084
 
6.0%

h_pct75
Text

Distinct6888
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:08.767816image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.4611396
Min length1

Characters and Unicode

Total characters167779
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1830 ?
Unique (%)4.9%

Sample

1st row30.82
2nd row68.5
3rd row106.69
4th row78.26
5th row*
ValueCountFrequency (%)
3830
 
10.2%
36.255
 
0.1%
2044
 
0.1%
35.641
 
0.1%
35.0839
 
0.1%
3037
 
0.1%
22.532
 
0.1%
2531
 
0.1%
2131
 
0.1%
2329
 
0.1%
Other values (6877)33440
88.9%
2025-11-10T21:56:08.979891image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
.33122
19.7%
221363
12.7%
317858
10.6%
414120
8.4%
113751
8.2%
512058
 
7.2%
611824
 
7.0%
711507
 
6.9%
811309
 
6.7%
910370
 
6.2%
Other values (3)10497
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)167779
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
.33122
19.7%
221363
12.7%
317858
10.6%
414120
8.4%
113751
8.2%
512058
 
7.2%
611824
 
7.0%
711507
 
6.9%
811309
 
6.7%
910370
 
6.2%
Other values (3)10497
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)167779
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
.33122
19.7%
221363
12.7%
317858
10.6%
414120
8.4%
113751
8.2%
512058
 
7.2%
611824
 
7.0%
711507
 
6.9%
811309
 
6.7%
910370
 
6.2%
Other values (3)10497
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)167779
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
.33122
19.7%
221363
12.7%
317858
10.6%
414120
8.4%
113751
8.2%
512058
 
7.2%
611824
 
7.0%
711507
 
6.9%
811309
 
6.7%
910370
 
6.2%
Other values (3)10497
 
6.3%

h_pct90
Text

Distinct7760
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:09.140867image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.4265468
Min length1

Characters and Unicode

Total characters166478
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1994 ?
Unique (%)5.3%

Sample

1st row47.51
2nd row98.03
3rd row#
4th row#
5th row*
ValueCountFrequency (%)
4310
 
11.5%
35.682
 
0.2%
92.2548
 
0.1%
38.0333
 
0.1%
36.232
 
0.1%
36.2430
 
0.1%
54.3429
 
0.1%
3027
 
0.1%
2226
 
0.1%
3526
 
0.1%
Other values (7749)32966
87.7%
2025-11-10T21:56:09.358265image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
.32675
19.6%
218070
10.9%
317897
10.8%
414910
9.0%
512975
 
7.8%
612483
 
7.5%
112270
 
7.4%
811652
 
7.0%
711637
 
7.0%
910615
 
6.4%
Other values (3)11294
 
6.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)166478
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
.32675
19.6%
218070
10.9%
317897
10.8%
414910
9.0%
512975
 
7.8%
612483
 
7.5%
112270
 
7.4%
811652
 
7.0%
711637
 
7.0%
910615
 
6.4%
Other values (3)11294
 
6.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)166478
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
.32675
19.6%
218070
10.9%
317897
10.8%
414910
9.0%
512975
 
7.8%
612483
 
7.5%
112270
 
7.4%
811652
 
7.0%
711637
 
7.0%
910615
 
6.4%
Other values (3)11294
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)166478
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
.32675
19.6%
218070
10.9%
317897
10.8%
414910
9.0%
512975
 
7.8%
612483
 
7.5%
112270
 
7.4%
811652
 
7.0%
711637
 
7.0%
910615
 
6.4%
Other values (3)11294
 
6.8%

a_pct10
Text

Distinct7333
Distinct (%)19.5%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:09.514345image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.953309
Min length1

Characters and Unicode

Total characters186289
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2083 ?
Unique (%)5.5%

Sample

1st row23520
2nd row51100
3rd row104950
4th row50410
5th row18270
ValueCountFrequency (%)
635
 
1.7%
31200240
 
0.6%
29120169
 
0.4%
24960120
 
0.3%
19760119
 
0.3%
31470103
 
0.3%
3536097
 
0.3%
4260086
 
0.2%
3264083
 
0.2%
3744066
 
0.2%
Other values (7322)35891
95.4%
2025-11-10T21:56:09.726366image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
048726
26.2%
322890
12.3%
418786
 
10.1%
216832
 
9.0%
514527
 
7.8%
614231
 
7.6%
112572
 
6.7%
712503
 
6.7%
912445
 
6.7%
812142
 
6.5%
Other values (2)635
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)186289
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
048726
26.2%
322890
12.3%
418786
 
10.1%
216832
 
9.0%
514527
 
7.8%
614231
 
7.6%
112572
 
6.7%
712503
 
6.7%
912445
 
6.7%
812142
 
6.5%
Other values (2)635
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)186289
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
048726
26.2%
322890
12.3%
418786
 
10.1%
216832
 
9.0%
514527
 
7.8%
614231
 
7.6%
112572
 
6.7%
712503
 
6.7%
912445
 
6.7%
812142
 
6.5%
Other values (2)635
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)186289
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
048726
26.2%
322890
12.3%
418786
 
10.1%
216832
 
9.0%
514527
 
7.8%
614231
 
7.6%
112572
 
6.7%
712503
 
6.7%
912445
 
6.7%
812142
 
6.5%
Other values (2)635
 
0.3%

a_pct25
Text

Distinct8572
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:09.863258image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.9641043
Min length1

Characters and Unicode

Total characters186695
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2611 ?
Unique (%)6.9%

Sample

1st row30660
2nd row72870
3rd row130950
4th row74720
5th row20950
ValueCountFrequency (%)
784
 
2.1%
31200110
 
0.3%
2912073
 
0.2%
3744055
 
0.1%
4160053
 
0.1%
3536052
 
0.1%
4368048
 
0.1%
3956046
 
0.1%
5995043
 
0.1%
4576042
 
0.1%
Other values (8561)36303
96.5%
2025-11-10T21:56:10.054826image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
048794
26.1%
320126
10.8%
419313
 
10.3%
515725
 
8.4%
615451
 
8.3%
214198
 
7.6%
713871
 
7.4%
812958
 
6.9%
912927
 
6.9%
112548
 
6.7%
Other values (2)784
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)186695
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
048794
26.1%
320126
10.8%
419313
 
10.3%
515725
 
8.4%
615451
 
8.3%
214198
 
7.6%
713871
 
7.4%
812958
 
6.9%
912927
 
6.9%
112548
 
6.7%
Other values (2)784
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)186695
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
048794
26.1%
320126
10.8%
419313
 
10.3%
515725
 
8.4%
615451
 
8.3%
214198
 
7.6%
713871
 
7.4%
812958
 
6.9%
912927
 
6.9%
112548
 
6.7%
Other values (2)784
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)186695
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
048794
26.1%
320126
10.8%
419313
 
10.3%
515725
 
8.4%
615451
 
8.3%
214198
 
7.6%
713871
 
7.4%
812958
 
6.9%
912927
 
6.9%
112548
 
6.7%
Other values (2)784
 
0.4%
Distinct10087
Distinct (%)26.8%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:10.206442image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0015954
Min length1

Characters and Unicode

Total characters188105
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3184 ?
Unique (%)8.5%

Sample

1st row43830
2nd row100640
3rd row164400
4th row106330
5th row26990
ValueCountFrequency (%)
1078
 
2.9%
4160064
 
0.2%
5995039
 
0.1%
5200039
 
0.1%
4900034
 
0.1%
3120033
 
0.1%
3744033
 
0.1%
4576029
 
0.1%
4784028
 
0.1%
5839027
 
0.1%
Other values (10076)36205
96.3%
2025-11-10T21:56:10.417470image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
049370
26.2%
418511
 
9.8%
316578
 
8.8%
616429
 
8.7%
516117
 
8.6%
115317
 
8.1%
714780
 
7.9%
813496
 
7.2%
913464
 
7.2%
212965
 
6.9%
Other values (2)1078
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)188105
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
049370
26.2%
418511
 
9.8%
316578
 
8.8%
616429
 
8.7%
516117
 
8.6%
115317
 
8.1%
714780
 
7.9%
813496
 
7.2%
913464
 
7.2%
212965
 
6.9%
Other values (2)1078
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)188105
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
049370
26.2%
418511
 
9.8%
316578
 
8.8%
616429
 
8.7%
516117
 
8.6%
115317
 
8.1%
714780
 
7.9%
813496
 
7.2%
913464
 
7.2%
212965
 
6.9%
Other values (2)1078
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)188105
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
049370
26.2%
418511
 
9.8%
316578
 
8.8%
616429
 
8.7%
516117
 
8.6%
115317
 
8.1%
714780
 
7.9%
813496
 
7.2%
913464
 
7.2%
212965
 
6.9%
Other values (2)1078
 
0.6%

a_pct75
Text

Distinct11787
Distinct (%)31.3%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:10.584020image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0784653
Min length1

Characters and Unicode

Total characters190996
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4116 ?
Unique (%)10.9%

Sample

1st row64110
2nd row142480
3rd row221910
4th row162780
5th row41760
ValueCountFrequency (%)
1365
 
3.6%
7530051
 
0.1%
4160040
 
0.1%
7297039
 
0.1%
7405035
 
0.1%
6240030
 
0.1%
5200028
 
0.1%
9564026
 
0.1%
8222026
 
0.1%
19188024
 
0.1%
Other values (11776)35945
95.6%
2025-11-10T21:56:10.848354image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
049800
26.1%
119691
 
10.3%
416817
 
8.8%
616144
 
8.5%
516044
 
8.4%
715504
 
8.1%
314541
 
7.6%
814197
 
7.4%
914000
 
7.3%
212893
 
6.8%
Other values (2)1365
 
0.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)190996
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
049800
26.1%
119691
 
10.3%
416817
 
8.8%
616144
 
8.5%
516044
 
8.4%
715504
 
8.1%
314541
 
7.6%
814197
 
7.4%
914000
 
7.3%
212893
 
6.8%
Other values (2)1365
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)190996
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
049800
26.1%
119691
 
10.3%
416817
 
8.8%
616144
 
8.5%
516044
 
8.4%
715504
 
8.1%
314541
 
7.6%
814197
 
7.4%
914000
 
7.3%
212893
 
6.8%
Other values (2)1365
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)190996
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
049800
26.1%
119691
 
10.3%
416817
 
8.8%
616144
 
8.5%
516044
 
8.4%
715504
 
8.1%
314541
 
7.6%
814197
 
7.4%
914000
 
7.3%
212893
 
6.8%
Other values (2)1365
 
0.7%

a_pct90
Text

Distinct13288
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-11-10T21:56:11.244102image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.12614
Min length1

Characters and Unicode

Total characters192789
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5016 ?
Unique (%)13.3%

Sample

1st row98810
2nd row203900
3rd row#
4th row#
5th row63900
ValueCountFrequency (%)
1932
 
5.1%
7405080
 
0.2%
19188048
 
0.1%
11303029
 
0.1%
7538026
 
0.1%
7910026
 
0.1%
10724025
 
0.1%
9431025
 
0.1%
20399023
 
0.1%
6373023
 
0.1%
Other values (13277)35372
94.1%
2025-11-10T21:56:11.459768image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
049517
25.7%
123544
12.2%
616191
 
8.4%
515479
 
8.0%
715433
 
8.0%
414884
 
7.7%
914233
 
7.4%
814231
 
7.4%
213854
 
7.2%
313491
 
7.0%
Other values (2)1932
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)192789
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
049517
25.7%
123544
12.2%
616191
 
8.4%
515479
 
8.0%
715433
 
8.0%
414884
 
7.7%
914233
 
7.4%
814231
 
7.4%
213854
 
7.2%
313491
 
7.0%
Other values (2)1932
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)192789
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
049517
25.7%
123544
12.2%
616191
 
8.4%
515479
 
8.0%
715433
 
8.0%
414884
 
7.7%
914233
 
7.4%
814231
 
7.4%
213854
 
7.2%
313491
 
7.0%
Other values (2)1932
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)192789
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
049517
25.7%
123544
12.2%
616191
 
8.4%
515479
 
8.0%
715433
 
8.0%
414884
 
7.7%
914233
 
7.4%
814231
 
7.4%
213854
 
7.2%
313491
 
7.0%
Other values (2)1932
 
1.0%

annual
Boolean

Constant  Missing 

Distinct1
Distinct (%)< 0.1%
Missing34943
Missing (%)92.9%
Memory size1.2 MiB
True
 
2666
(Missing)
34943 
ValueCountFrequency (%)
True2666
 
7.1%
(Missing)34943
92.9%
2025-11-10T21:56:11.511223image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

hourly
Boolean

Constant  Missing 

Distinct1
Distinct (%)0.6%
Missing37447
Missing (%)99.6%
Memory size1.1 MiB
True
 
162
(Missing)
37447 
ValueCountFrequency (%)
True162
 
0.4%
(Missing)37447
99.6%
2025-11-10T21:56:11.549146image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Interactions

2025-11-10T21:56:02.155062image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Correlations

2025-11-10T21:56:11.577017image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
areaarea_typeo_group
area1.0001.0000.021
area_type1.0001.0000.032
o_group0.0210.0321.000

Missing values

2025-11-10T21:56:02.281629image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
A simple visualization of nullity by column.
2025-11-10T21:56:02.521508image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-11-10T21:56:02.699562image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

areaarea_titlearea_typeprim_statenaicsnaics_titlei_groupown_codeocc_codeocc_titleo_grouptot_empemp_prsejobs_1000loc_quotientpct_totalpct_rpth_meana_meanmean_prseh_pct10h_pct25h_medianh_pct75h_pct90a_pct10a_pct25a_mediana_pct75a_pct90annualhourly
01alabama2al0cross-industrycross-industry123500-0000all occupationstotal2091480010001NaNNaN26.61553500.311.3114.7421.0730.8247.512352030660438306411098810NaNNaN
11alabama2al0cross-industrycross-industry123511-0000management occupationsmajor1102400.952.7080.74NaNNaN57.051186700.724.5735.0348.3968.598.035110072870100640142480203900NaNNaN
21alabama2al0cross-industrycross-industry123511-1011chief executivesdetailed83017.60.3960.29NaNNaN99.612071904.650.4662.9679.04106.69#104950130950164400221910#NaNNaN
31alabama2al0cross-industrycross-industry123511-1021general and operations managersdetailed323701.615.4760.67NaNNaN64.81347901.624.2435.9251.1278.26#5041074720106330162780#NaNNaN
41alabama2al0cross-industrycross-industry123511-1031legislatorsdetailed11208.70.5333.1NaNNaN*365703.8*****1827020950269904176063900TrueNaN
51alabama2al0cross-industrycross-industry123511-2011advertising and promotions managersdetailed5035.60.0220.16NaNNaN62.591301804.140.1841.5964.2269.5772.448357086500133570144710150670NaNNaN
61alabama2al0cross-industrycross-industry123511-2021marketing managersdetailed16607.50.7920.32NaNNaN62.821306603.131.4240.3654.3178.64105.296536083940112960163580219000NaNNaN
71alabama2al0cross-industrycross-industry123511-2022sales managersdetailed43806.42.0950.54NaNNaN65.841369503.831.7840.2952.2878.55#6610083790108740163390#NaNNaN
81alabama2al0cross-industrycross-industry123511-2032public relations managersdetailed41019.70.1980.4NaNNaN54.461132806.425.3236.844.7361.9188.62526707654093040128770184330NaNNaN
91alabama2al0cross-industrycross-industry123511-2033fundraising managersdetailed2109.90.10.42NaNNaN52.09108350626.6128.9741.1553.293.36553506026085600110650194180NaNNaN
areaarea_titlearea_typeprim_statenaicsnaics_titlei_groupown_codeocc_codeocc_titleo_grouptot_empemp_prsejobs_1000loc_quotientpct_totalpct_rpth_meana_meanmean_prseh_pct10h_pct25h_medianh_pct75h_pct90a_pct10a_pct25a_mediana_pct75a_pct90annualhourly
3759978virgin islands3vi0cross-industrycross-industry123553-3051bus drivers, schooldetailed5016.31.4860.59NaNNaN21.92455908.116.9118.2318.9225.0231.643518037920393605205065820NaNNaN
3760078virgin islands3vi0cross-industrycross-industry123553-3053shuttle drivers and chauffeursdetailed602.51.8151.22NaNNaN16.5343200.51314.8616.9717.8419.292703030910353003711040120NaNNaN
3760178virgin islands3vi0cross-industrycross-industry123553-5011sailors and marine oilersdetailed110283.16315.55NaNNaN14.412996018.811.9512.5113.3815.5218.962485026030278303228039430NaNNaN
3760278virgin islands3vi0cross-industrycross-industry123553-5021captains, mates, and pilots of water vesselsdetailed12012.33.65315.92NaNNaN*************NaNNaN
3760378virgin islands3vi0cross-industrycross-industry123553-6031automotive and watercraft service attendantsdetailed4032.21.1721.84NaNNaN13.42787010.911.211.511.5612.2919.812330023920240402556041200NaNNaN
3760478virgin islands3vi0cross-industrycross-industry123553-7051industrial truck and tractor operatorsdetailed4028.81.2220.23NaNNaN16.713476015.814.7715.3615.361718.913071031950319503536039330NaNNaN
3760578virgin islands3vi0cross-industrycross-industry123553-7061cleaners of vehicles and equipmentdetailed5024.21.5680.65NaNNaN14.0129140410.51213.1214.6318.812184024960272903043039120NaNNaN
3760678virgin islands3vi0cross-industrycross-industry123553-7062laborers and freight, stock, and material movers, handdetailed4807.114.2410.74NaNNaN16.05333901.813.451415.8117.6618.712797029120328903674038910NaNNaN
3760778virgin islands3vi0cross-industrycross-industry123553-7064packers and packagers, handdetailed12011.93.5070.9NaNNaN13.69284703.710.7610.9411.9814.9317.992238022750249203106037410NaNNaN
3760878virgin islands3vi0cross-industrycross-industry123553-7065stockers and order fillersdetailed4406.612.8160.71NaNNaN13.73285501.211.0811.7713.8514.2716.932304024480288002968035210NaNNaN